Digital transformation of the Public Distribution System

Digital Transformation of the Public Distribution

System: Need for impact evaluation using a Supply

Chain Perspective

The public distribution system (PDS) in India is the largest food security system of its kind in the world. It is the primary delivery vehicle to fulfil the mandate of the National Food Security Act (NFSA) 2013 of providing subsidised food grains to up to 75% of the rural and 50% of the urban population. At present, commodities worth INR 150 billion are distributed annually to around 160 million families through more than half a million fair price shops (FPSs) in the PDS. [1]

There are many sources of inefficiency associated with the PDS. An important problem is the inaccurate identification of beneficiary households, which has resulted in eligible households being excluded (exclusion errors) and some ineligible households being included (inclusion errors) in the system. As of 2016, as many as 21.6 million ‘bogus’ ration cards were detected in the PDS. [2] At present, these fictitious cards are identified during surprise audits and there is no in-built mechanism to either identify them on a routine basis or to check their recreation. Another major shortcoming of the PDS is that beneficiaries often do not receive their full entitlement. This can happen either due to the wilful diversion of grains by FPS owners to the open market or the non-availability of grains owing to poor planning of inventory and shipments because of lack of visibility across different levels of the PDS supply chain. Estimates suggest that only half of the grains purchased by the PDS reach the intended user. [3]

In recent years, the central government, with the help of several state governments, has embarked on an ambitious initiative towards the end-to-end digital transformation of the PDS supply chain to address these sources of inefficiency. A key component of this initiative is the digitisation of the beneficiary database and linking ration cards to Aadhaar numbers, referred to as ‘Aadhaar seeding’. This process intends to weed out duplicate cards in the system and also prevent the creation of new ones in the future. Another key component, complementary to Aadhaar seeding, is the use of point of sale (POS) devices at FPSs. These devices help to reduce the diversion of grains by enabling

authentication of beneficiaries through linkage to Aadhaar and biometric details,

accurate recording of the quantity of grains sold to beneﬁciaries through the integrated weighing machine, and

uploading of transaction data to the central server.

About 62% of ration cards across the country have been seeded with Aadhaar details [4] and around 17% of about 0.53 million FPSs are currently POS enabled. [5]

However, early evidence suggests that all the above intended benefits may not be realised due to operational glitches. Firstly, there is a risk of exclusion error due to either incorrect mapping of ration card to Aadhaar details or deactivation of Aadhaar numbers for a multitude of reasons, for instance, document verification failure or imprecise capture of biometric details. [6] Secondly, beneficiaries could lose their entitlements because of authentication failures due to either poor quality of fingerprints or even poor Internet connectivity. Finally, other problems that have been encountered during implementation are frequent breakdowns of POS machines and the consequent need for frequent maintenance.

Given these risks, there is an urgent need to rigorously evaluate whether the actual benefits outweigh the costs of implementation. A few initial attempts have been made to quantify the gains, based largely on the reduction in purchase of commodities before and after implementation. The government of Andhra Pradesh, for example, claimed an estimated savings of INR 2.46 billion from the implementation of end-to-end computerisation. [7] However, such simple methods have two major drawbacks. Firstly, they fail to compare how the consumption of commodities would have changed in the absence of digitisation. Such comparisons require a random assignment of units to ‘treatment’ and ‘control’ groups to establish a causal relationship between digitisation and its benefits. However, political considerations render field experiments in this context difficult to implement. An alternative approach that uses observational data is to construct a control group (by matching FPSs that have similar characteristics and using the ones that have not been chosen for implementation as ‘control’ observations) and comparing them against the ‘treatment’ observations over time. Secondly, current policy discourse does not discuss whether real-time data such as sales and inventory information, now made available due to the use of POS devices, is being utilised to make better supply chain decisions such as inventory levels, frequency of shipments and order quantities.

We believe that there is a pressing need for such a comprehensive evaluation exercise, before further scaling up implementation. Considering the heterogeneity in implementation approaches across various states, this learning from different experiences and the results from the analysis could inform modifications in further implementation.

This article is written by Maya Ganesh based on an ongoing research with Prof. Sarang Deo and Prof. Sripad Devalkar.